Differential methylation of G-protein coupled receptor signaling genes in gastrointestinal neuroendocrine tumors

Abstract Neuroendocrine tumors (NETs) of the small intestine undergo large chromosomal and methylation changes. The objective of this study was to identify methylation differences in NETs and consider how the differentially methylated genes may impact patient survival. Genome-wide methylation and chromosomal copy number variation (CNV) of NETs from the small intestine and appendix were measured. Tumors were divided into three molecular subtypes according to CNV results: chromosome 18 loss (18LOH), Multiple CNV, and No CNV. Comparison of 18LOH tumors with MultiCNV and NoCNV tumors identified 901 differentially methylated genes. Genes from the G-protein coupled receptor (GPCR) pathways are statistically overrepresented in the differentially methylated genes. One of the highlighted genes from the GPCR pathway is somatostatin (SST), a clinical target for NETs. Patient survival based on low versus high methylation in all samples identified four significant genes (p < 0.05) OR2S2, SMILR, RNU6-653P, and AC010543.1. Within the 18LOH molecular subtype tumors, survival differences were identified in high versus low methylation of 24 genes. The most significant is TRHR (p < 0.01), a GPCR with multiple FDA-approved drugs. By separating NETs into different molecular subtypes based on chromosomal changes, we find that multiple GPCRs and their ligands appear to be regulated through methylation and correlated with survival. These results suggest opportunities for better treatment strategies for NETs based on molecular features

Integrated Molecular Characterization of Intraductal Papillary Mucinous Neoplasms: An NCI Cancer Moonshot Precancer Atlas Pilot Project

Intraductal papillary mucinous neoplasms (IPMN) are cystic precursor lesions to pancreatic ductal adenocarcinoma (PDAC). IPMNs undergo multistep progression from low-grade (LG) to high-grade (HG) dysplasia, culminating in invasive neoplasia. While patterns of IPMN progression have been analyzed using multiregion sequencing for somatic mutations, there is no integrated assessment of molecular events, including copy-number alterations (CNA) and transcriptional changes that accompany IPMN progression. We performed laser capture microdissection on surgically resected IPMNs of varying grades of histologic dysplasia obtained from 23 patients, followed by whole-exome and whole-transcriptome sequencing. Overall, HG IPMNs displayed a significantly greater aneuploidy score than LG lesions, with chromosome 1q amplification being associated with HG progression and with cases that harbored co-occurring PDAC. Furthermore, the combined assessment of single-nucleotide variants (SNV) and CNAs identified both linear and branched evolutionary trajectories, underscoring the heterogeneity in the progression of LG lesions to HG and PDAC. At the transcriptome level, upregulation of MYC-regulated targets and downregulation of transcripts associated with the MHC class I antigen presentation machinery as well as pathways related to glycosylation were a common feature of progression to HG. In addition, the established PDAC transcriptional subtypes (basal-like and classical) were readily apparent within IPMNs. Taken together, this work emphasizes the role of 1q copy-number amplification as a putative biomarker of high-risk IPMNs, underscores the importance of immune evasion even in noninvasive precursor lesions, and reinforces that evolutionary pathways in IPMNs are heterogenous, comprised of both SNV and CNA-driven events. Significance: Integrated molecular analysis of genomic and transcriptomic alterations in the multistep progression of IPMNs, which are bona fide precursors of pancreatic cancer, identifies features associated with progression of low-risk lesions to high-risk lesions and cancer, which might enable patient stratification and cancer interception strategies

FIGURE 1 from Integrated Molecular Characterization of Intraductal Papillary Mucinous Neoplasms: An NCI Cancer Moonshot Precancer Atlas Pilot Project

Genomic landscapes of IPMN lesions. A, SNVs identified in KRAS and GNAS in LG and HG IPMNs. Dark purple: somatic mutations detected for KRAS and GNAS. Light purple: mutations detected by retesting. B, SNVs and CNAs identified in ND, LG, HG, and PDAC regions and classified by relevant PDAC-related pathways. For A and B, samples were arranged by histological type and labeled at the top of each heat map.</p

FIGURE 3 from Integrated Molecular Characterization of Intraductal Papillary Mucinous Neoplasms: An NCI Cancer Moonshot Precancer Atlas Pilot Project

Inferred evolutionary trajectory derived from CNAs. Cases showing linear (A) and branched (B) evolution are depicted. For each case, evolutionary tree and segmentation plots are shown with HapLOHseq calls represented in lavender background. Branches are drawn to scale based on the number of CNA events. Chromosomal aberrations associated to the branch with the largest HG clone are shown. Red indicates gains and blue losses. Patient IDs highlighted in red indicate cases with coexisting PDAC. SNVs associated with each branch are labeled. Red arrow labels the branch with larger HG clone.</p

Supplementary Figure 1 from Integrated Molecular Characterization of Intraductal Papillary Mucinous Neoplasms: An NCI Cancer Moonshot Precancer Atlas Pilot Project

Schematic representation of the strategy employed</p

Supplementary Table 1 from Integrated Molecular Characterization of Intraductal Papillary Mucinous Neoplasms: An NCI Cancer Moonshot Precancer Atlas Pilot Project

List of compartments dissected by LCM</p

Supplementary Table 2 from Integrated Molecular Characterization of Intraductal Papillary Mucinous Neoplasms: An NCI Cancer Moonshot Precancer Atlas Pilot Project

Comparison in MAF and sequencing depth between a targeted and WES approach.</p

Supplementary Table 3 from Integrated Molecular Characterization of Intraductal Papillary Mucinous Neoplasms: An NCI Cancer Moonshot Precancer Atlas Pilot Project

Correlation between PDAC molecular suptypes and 1q amplification in TCGA data</p